Auto harassment monitoring system

ABSTRACT

Methods, systems, and computer programs are provided for identifying an abusive player in a game. One method includes receiving gameplay data for a player during gameplay of the game. The method includes processing a plurality of game mechanics of the game as the player provides input for one or more of said plurality of game mechanics. The method includes processing abusive action scores for each of the plurality of game mechanics. The abusive action scores have a number of tagged actions that are inconsistent with predefined use of said plurality of game mechanics based a game context of the gameplay of the game. The method includes qualifying the player as abusive in regard to one or more of the plurality of game mechanics based on one or more of the abusive actions scores exceeding a threshold during a session of the gameplay of the game.

BACKGROUND 1. Field of the Disclosure

The present disclosure relates generally to dynamic monitoring gameplayof a player, and more particularly to methods and systems foridentifying whether a player is an abusive player.

2. Description of the Related Art

The video game industry has seen many changes over the years and hasbeen trying to find ways to enhance a player's gaming experience so thatengagement by the player is increased or maintain. An increase in aplayer's engagement level in video games can result in higher retentionlevels and an increase video game revenue. To this end, developers havebeen seeking ways to develop sophisticated operations to enhance aplayer's gaming experience.

A growing trend in video game industry is online harassment andcyberbullying in video games by players commonly referred to as abusiveplayers, bad faith players, or griefers. For example, an abusive playercan be a player in a multiplayer video game who deliberately irritates,annoys, and harasses other players within the game, using aspects of thegame in unintended ways. Accordingly, this prevents other players (e.g.,good faith players) from becoming fully immersed in their gameplay andfrom fully enjoying their gaming experience. Unfortunately, identifyingabusive players and monitoring their actions in the gameplay may bedifficult and utilize a significant amount of resources. As a result,the actions by abusive players in a gameplay may interfere with thegameplay of other players which may lead to a decrease in playerengagement in video games, and in turn lead to players playing videogames less frequently.

It is in this context that implementations of the disclosure arise.

SUMMARY

Implementations of the present disclosure include devices, methods andsystems relating to identifying abusive players in gameplay from among aplurality of players playing the game. In some embodiments, abusive actscommitted by the player are tagged during the gameplay of a player todetermine an abusive action score for a corresponding game mechanic Insome embodiments, if the abusive action score exceeds a threshold value,the player is identified as an abusive player and remedial measures maybe taken to prevent the player from acting abusively in the gameplay. Insome embodiments, a warning notification can be generated to notify theplayer during the gameplay that the player has been identified as anabusive player, or the game mechanics associated with the gameplay ofthe player can be limited.

In one embodiment, a method for identifying an abusive player in a gameis provided. The method includes receiving gameplay data for a playerduring gameplay of the game. The method includes processing a pluralityof game mechanics of the game as the player provides input for one ormore of said plurality of game mechanics. The method includes processingabusive action scores for each of the plurality of game mechanics. Theabusive action scores have a number of tagged actions that areinconsistent with predefined use of said plurality of game mechanicsbased a game context of the gameplay of the game. The method includesqualifying the player as abusive in regard to one or more of theplurality of game mechanics based on one or more of the abusive actionsscores exceeding a threshold during a session of the gameplay of thegame. In some cases, the player may be identified as abusive forspecific types of games or for specific types of game mechanics.

In another embodiment, a non-transitory computer-readable storage mediumstoring a computer program is provided. The computer-readable storagemedium includes program instructions for receiving gameplay data for aplayer during gameplay of the game, and program instructions forprocessing a plurality of game mechanics of the game as the playerprovides input for one or more of said plurality of game mechanics. Thecomputer-readable storage medium includes program instructions forprocessing abusive action scores for each of the plurality of gamemechanics. The abusive action scores have a number of tagged actionsthat are inconsistent with predefined use of said plurality of gamemechanics based on a game context of the gameplay of the game.Additionally, the computer-readable storage medium includes programinstructions for qualifying the player as abusive in regard to one ormore of the plurality of game mechanics based on one or more of theabusive actions scores exceeding a threshold during a session of thegameplay of the game.

Other aspects and advantages of the disclosure will become apparent fromthe following detailed description, taken in conjunction with theaccompanying drawings, illustrating by way of example the principles ofthe disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may be better understood by reference to the followingdescription taken in conjunction with the accompanying drawings inwhich:

FIG. 1 illustrates an embodiment of a system configured to execute agameplay for a plurality of players and to send a warning notificationto the player that is identified as an abusive player, in accordancewith an implementation of the disclosure.

FIG. 2A illustrates an embodiment of a gameplay analytics enginereceiving gameplay data from a game played by a player and processingthe gameplay data to determine whether the actions of the playerassociated with the game mechanics are characterized as abusive, inaccordance with an implementation of the disclosure.

FIG. 2B illustrates an embodiment of a method for using an abuseindicator model to generate a gameplay player summary table using gamecontext, gameplay data from a plurality of players, inconsistentactions, and player tagged feedback as inputs, in accordance with animplementation of the disclosure.

FIG. 3 illustrates an embodiment of a system generating a player profilefor a given player using player gameplay data and a player profilemodel, in accordance with an implementation of the disclosure.

FIG. 4A illustrates an embodiment of a game mechanics grid for a gameplayed by a player, in accordance with an implementation of thedisclosure.

FIG. 4B is an embodiment illustrating a timeline with a game mechanicsgrid being continuously updated throughout a game session, in accordancewith an implementation of the disclosure.

FIG. 5 is an embodiment illustrating correlating accolades that arepresented to a player during a game to a specific game context in thegame, in accordance with an implementation of the disclosure.

FIG. 6 illustrates an embodiment of a player accolades table for aplurality of players, in accordance with an implementation of thedisclosure.

FIG. 7 illustrates a method for identifying an abusive player in a gameduring a game session, in accordance with an implementation of thedisclosure.

FIG. 8 illustrates components of an example device 800 that can be usedto perform aspects of the various embodiments of the present disclosure.

DETAILED DESCRIPTION

The following implementations of the present disclosure provide devices,methods, and systems for identifying an abusive player in a game duringa session. In particular, the present disclosure identifies abusiveplayers from among a plurality of players playing a game by tracking andtagging acts in the gameplay that are characterized as abusive behavior.Once the abusive player is identified, the abusive player is notifiedvia a warning notification and is requested to comply with the warningnotification. In other cases, the player may be penalized in a number ofways or game mechanics associated with the gameplay of the player can belimited.

The embodiments described herein can be used to encourage players torefrain from abusive behavior. Abusive behavior can have negativeimpacts on gaming systems, as more processing power and resources areused up by players that have little to no intent on playing games forenjoyment, but instead act to frustrate other players. By way ofexample, in online and streaming gaming, servers are used to satisfybandwidth requirements of all players. Although server and processingresources have improved significantly over the years, supplyingprocessing power and system resources to players who engaging in abusivegameplay activities will unnecessarily increase the strain on resourcesor increase the power resources required to keep abusive players online.In some cases, the strain on game resources can have performance impactson other players that play games as intended.

In one embodiment, a method is disclosed that enables identifying anabusive player in a game played by a plurality of players. The methodincludes receiving gameplay data for a player during gameplay of thegame. The method may further include processing a plurality of gamemechanics of the game as the player provides input for one or more ofsaid plurality of game mechanics. The method may further includeprocessing abusive action scores for each of the plurality of gamemechanics. The abusive action scores have a number of tagged actionsthat are inconsistent with predefined use of said plurality of gamemechanics based a game context of the gameplay of the game. The methodincludes qualifying the player as abusive in regard to one or more ofthe plurality of game mechanics based on one or more of the abusiveactions scores exceeding a threshold during a session of the gameplay ofthe game. It will be obvious, however, to one skilled in the art thatthe present disclosure may be practiced without some or all of thespecific details presently described. In other instances, well knownprocess operations have not been described in detail in order not tounnecessarily obscure the present disclosure.

In accordance with one embodiment, a system is disclosed for identifyingan abusive player in a game such as an online multiplayer video game.For example, the game may be a particular game being played live duringan E-sports event, group game play, or team play. In one embodiment, thesystem may include a plurality of players connected over a network. Theplurality of players may be playing a multiplayer video game orcompeting against one another in a live gaming event. In someembodiments, one or more data centers and game servers can execute thegame and enable connections to the players when hosting the video game.The one or more game servers of the one or more data centers may beconfigured to receive, process, and execute data from a plurality ofplayers.

In some embodiments, during the gameplay, abusive players can beidentified from among the plurality of players playing the video game.For example, an abusive player may be a player who deliberatelyirritates and harasses others players in a game, or uses aspects of thegame in unintended ways. In one embodiment, a warning notification canbe generated to notify the abusive player of their abusive acts duringthe gameplay. The warning notification may used to put the abusiveplayer on notice that the player has been identified as an abusiveplayer and request the abusive player to comply with the warningnotification (e.g., do not kill your teammate, follow your leader,follow the team plan, don't avoid scoring points, do not spam chatchannel, do not hit ball out of bounds, etc.).

In accordance with another embodiment, a system is disclosed foridentifying an abusive player in a game and generating a warningnotification for the player that is identified as abusive player. In oneembodiment, the system enables receiving gameplay data for a gameplay ofa player. The gameplay data can be processed to identify various gamemechanics associated with the gameplay of the player. The features fromthe game mechanics can be extracted and classified using one or moreclassifiers. In some embodiments, the classified features can be used byan abuse indicator model to predict whether the actions of the playerduring the gameplay are characterized as abusive behavior or actions.

In one embodiment, a player profile model can be used to generate aprofile associated with a player. In some embodiments, the profile ofthe player may include the player's gameplay tendencies which can beused by the player profile model to determine whether the actions of aplayer during a gameplay are characterized as abusive behavior. Forexample, the player profile model may determine that a player is anexpert in sword combat and the player's weapon preference is combatscenes is a sword. When analyzing game mechanics of a player thatinvolves attacking enemies, the abuse indicator model may take intoconsideration the profile of the player (e.g., sword expert) todetermine whether the actions of the player are characterized abusive.In other words, if the player chooses to use a sword rather than a gunto attack an enemy during a gameplay even though the use of a gun wouldgenerally be more effective, the abuse indicator model may take intoconsideration that the player is an expert in sword combat and will notcharacterize the actions of the player as abusive.

In accordance with another embodiment, accolades (positive or negative)may be given to a player during the gameplay of the player or after agame session ends. A player may give accolades to other playersparticipating in the gameplay, e.g., teammate, player on opposing teams,etc. In some embodiments, a player who has a track record of receivingpositive accolades may help distinguish the player as being a good faithplayer rather than an abusive player. Conversely, a player who has atrack record of receiving negative accolades may help distinguish theplayer as being an abusive player rather than a good faith player. Inone embodiment, the player accolades may be used by the abuse indicatormodel to help predict whether the game mechanics associated with thegameplay of the player are characterized as abusive.

With the above overview in mind, the following provides several examplefigures to facilitate understanding of the example embodiments.

FIG. 1 illustrates an embodiment of a system configured to execute agameplay for a plurality of players 102 a-102 b and to send a warningnotification 108 to a player that is identified as an abusive player. Inone example, an abusive player may be one that abuses game mechanic oracts inconsistent with advancement in a game. In another example, theabusive player may be abusive toward another player. The abusivebehavior may be, for example, intentionally not helping a team playercomplete a task, taking actions to reduce the game actions of anotherplayer, continued interference toward another player, or generallyacting inconsistent with intended use of game actions or game mechanicsto advance or enjoy a game.

In one embodiment, FIG. 1 illustrates players 102 a-102 b, a data center110, a game server 112, and a network 114. Players 102 a-102 b arecoupled to and can communicate with the data center 110 and the gameserver 112 through the network 114. The system of FIG. 1 may be referredto as a cloud gaming system, where multiple data centers 110 and gameservers 112 may work together to provide wide access to users andplayers 102 in a distributed and seamless fashion.

In some embodiments, the players 102 a-102 b can be playing amultiplayer game where they are teammates or on opposing teams competingagainst one another. The players 102 a-102 b can be configured to sendgame commands to the data center 110 and the game server 112 through thenetwork 114. In addition, the players 102 a-102 b can be configured toreceive encoded video streams and decode the video streams received bythe data center 110 and game server 112. In some embodiments, the videostreams may be presented to players 102 a-102 b on a display and/or aseparate device such as a monitor or television. In some embodiments,the devices of the players can be any connected device having a screenand internet connections.

For example, FIG. 1 illustrates an embodiment of players 102 a-102 bplaying a game that is displayed on monitors 106 a-106 b, respectively.In the game, players 102 a-102 b are on the same team competing againstan opposing team in a volleyball tournament. As shown on the monitors106 a-106 b, players 102 a-102 b are represented by avatars 104 a-104 b,respectively, which shows them competing against players on the opposingteam, e.g., 105 a-105 b. During the gameplay, the system automaticallymonitors the game mechanics and various actions occurring in thegameplay and determines whether any of the acts of the players 102 a-102b are characterized as abusive.

In some embodiments, the system may identify one or more players in thegameplay as abusive players by determining whether their abusive actionscore for a particular game mechanic exceeds a threshold value. In someembodiments, the abusive action score is determined based on the totalnumber of abusive acts committed by the player during a game session. Inone embodiment, when a player 102 is identified as an abusive player, awarning notification 108 is generated and can appear on the monitor 106of the player to notify the player that the player has been identifiedas an abusive player. In some embodiments, the warning notification 108may include specific instructions requesting the abusive player tocomply with a specific request or to restrain from performing abusiveacts. For example, as shown in FIG. 1, player 102 a is identified as anabusive player. A warning notification 108 my appear on the monitor 106a of the abusive player (e.g., player 102 a) notifying the player thatthe player has been identified as an abusive player. As illustrated, thewarning notification 108 includes the message, “Warning! You areidentified as an abusive player. Don't hit ball out of bounds.”Accordingly, the warning notification 108 may discourage abusive playersfrom playing the game in ways that intentionally interfere with thegameplay of others so that the gameplay is enjoyable to all the playersparticipating in the game. In some embodiments, if the abusive playerdoes not comply with the request in the warning notification, otherdisciplinary measures may be taken to prevent the player form performingthe abusive acts.

FIG. 2A illustrates an embodiment of a gameplay analytics engine 201receiving gameplay data 222 from a game played by a player 102 andprocessing the gameplay data 222 to determine whether the actions of theplayer associated with the game mechanics 206 (e.g., points scored,prisoner rescued, enemies attacked) are characterized as abusive. Asshown in FIG. 2, the system includes the gameplay analytics engine 201that is configured to receive gameplay data 222 as a game is beingplayed by the players 102. In one embodiment, the gameplay analyticsengine 201 may include an operation for extracting player gameplay data204 and an operation for processing game mechanics data 206 from thegameplay data 222. After processing the game mechanics data 206, thegameplay analytics engine 201 may include a feature extraction 208operation that is configured to receive the game mechanics data 206 toidentify various features in the game mechanics. After the featureextraction 208 identifies the features associated with the gamemechanics, a classifier 210 operation may be configured to classify thefeatures using one or more classifiers.

In some embodiments, the gameplay analytics engine 201 includes an abuseindicator model 212 that is configured to receive the classifiedfeatures from the classifier 210, data from the game context 202,inconsistent actions 228, and player tagged feedback 230. Using theclassified features, the game context data, the inconsistent actions,and the player tagged feedback as inputs, the abuse indicator model 212can be used to determine whether the actions of the player 102 in thegame are characterized as abusive actions. A threshold processor 214operation can use the abuse indicator model 212 determine whether theactions of the player 102 in the gameplay exceeds a specified thresholdvalue. The output of the threshold processor 214 can be received by agameplay penalizer 216 operation and a notification engine 218 operationas an input. In one embodiment, using data from the gameplay penalizer216 operation and the notification engine 218, a game logic 220operation can be used make changes to the game code to change variousoperational features associated with the gameplay.

In one embodiment, the system can process gameplay data 222 and extractdata for a particular player (e.g., Player 1) to analyze the player'sgameplay data. In one embodiment, the gameplay data 222 may include gametelemetry data and gameplay metadata associated with each player 102playing the game. The gameplay metadata may include coded information,such as state data that identifies all of the actions, inputs, and movesmade by the player 102 during player's 102 gameplay session.

In some embodiments, the system can be configured to process andidentify the game mechanics 206 associated with the gameplay of theplayer 102. In one embodiment, the game mechanics are the basic actions,processes, rules, and control mechanisms that make up gameplay for avideo game. For example, the game mechanics for a game may includevarious actions such as jumping, leaping over obstacles, fightingenemies, defending against enemies, solving puzzles, managing resources.For each game, the game mechanics may vary and be based on theparticular action scene that the player is playing. The system mayinclude an operation that can process and identify the game mechanics206 and actions being performed by the player 102 during the gameplay ofthe player. For example, a player 102 may be playing a fighting game andthe operation can process and identify various game mechanics 206associated with the game such as scoring points, attacking enemies,supporting teammates, etc.

In some embodiments, the feature extraction 208 operation is configuredto process the game mechanics 206 data to identify and extract featuresassociated with the game mechanics 206 performed by the player 102during the gameplay. By way of example, these features may include whatthe player is doing in the gameplay such as how the player scored points(e.g., enemies killed, kill assist, flags captured, etc.), how theplayer attacked their enemies (e.g. sword, knife, rifle, grenade, etc.),how the player support teammates (e.g., helping teammate defend againstenemy attacks, acquiring new weapons for team, supplying teammates withammunition etc.).

After the feature extraction 208 operation processes and identifies thefeatures from the game mechanics, the classifier 210 is configured toclassify the features using one or more classifiers. In one embodiment,the features are labeled using a classification algorithm for furtherrefining by the abuse indicator model 212. For example, during a gamesession, the player 102 may be in a battle scene fighting enemysoldiers. The features associated gameplay may include the playermissing multiple targets when shooting at enemy soldiers, the playerusing a knife in combat to fight rather than using a gun, the player notdefending themself when being attacked by enemy soldiers, the player notaiding teammates when the teammates are in need of help, etc. Thesenoted features can be classified by the classifier 210 as being abusiveacts (e.g., failing intentionally, misuse of game tools or gameobjectives, etc.).

In some embodiments, the abuse indicator model 212 can be configured toreceive as inputs the classified features from the classifier 210, thegame context 202, the inconsistent actions 228 associated with gameplaygame mechanics 226, and the player tagged feedback 230. In anotherembodiment, other inputs that are not direct inputs or lack ofinput/feedback, may also be taken as inputs to the abuse indicator model212. The abuse indicator model 212 may use a machine learning model topredict whether the actions of the player 102 are characterized asabusive and to determine an abusive action score associated with thegame mechanics in the gameplay.

In some embodiments, the game context 202 may be used as an input forthe abuse indicator model 212 so that the model knows what is going onin the game. The game context 202 may include data associated thecontext of the game, characters in the gameplay, current state of thegameplay, and the upcoming scenes. In one embodiment, the gameplay gamemechanics 226 may include all of the game mechanics associated with thegame that the player 102 is playing. Each of the gameplay game mechanics226 may include a plurality of inconsistent actions 228 that arepredefined to be inconsistent with how the game is intended to beplayed. For example, the inconsistent actions 228 may include variousactions that are contrary with the intent of the gaming activity andtends to irritate or harass other players in the game.

In some embodiments, the player tagged feedback 230 may include feedbackprovided by other players during the gameplay. The player taggedfeedback 230 can include various actions committed by the player duringthe gameplay that the other players in the game identify as beinginconsistent actions. For example, a player may be playing a basketballgame and only shoots the ball from half-court and never defends anopposing player when on defense. These actions by the player can betagged by the player's teammates as inconsistent actions since it iscontrary with the intent of the game (e.g., scoring points, playingdefense). Accordingly, the player tagged feedback 230 can be used as aninput for the abuse indicator model 212 so that the model understandsand learns what actions can be characterized as abusive.

In some embodiments, the threshold processor 214 operation can use theabuse indicator model 212 to determine whether the game mechanicsassociated with the gameplay of the player 102 exceeds a specifiedthreshold value. In one embodiment, the threshold value may bedetermined by a developer and vary on the specific type of gamemechanic. Using the abusive action score obtained from the abuseindicator model 212, the threshold processor 214 operation can determinewhether the abusive action score for a specific game mechanic exceedsthe corresponding threshold value. For example, the gameplay of a player102 includes the game mechanic involving a player attacking enemysoldiers. The abuse indicator model 212 can be used to determine thatthe abusive action score for the game mechanic is 2.2. Since thethreshold value for the game mechanic is 2.0, the abusive action scoreexceeds the threshold value and the player can be identified as anabusive player. Accordingly, appropriate remedial measures may be takenby the notification engine 218 and the gameplay penalizer 216 operation.

In some embodiments, when a player is identified as an abusive player(e.g., abusive score exceeds threshold value), the notification engine218 can be configured to generate a warning notification 108 to notifythe player that the player has been identified as an abusive player. Insome embodiments, the warning notification 108 may request the abusiveplayer to comply with a specific request (e.g., don't spam chat channel)In some embodiments, when a player is identified as an abusive player,the gameplay penalizer 216 operation can be configured to limit variousgame mechanics associated with the gameplay of the player (e.g.,limiting frequency of emoticon use, limiting frequency of chat use,limiting frequency of weapon use, etc.) or to disable the game mechanicsso that the player is unable to use it anymore. For example, a playermay be identified as an abusive player for overusing their weaponirrespective of having visible targets (e.g., weapon spamming) In thisexample, the context of game play is used as an input to determinewhether the action may be abusive. Accordingly, the gameplay penalizer216 can limit the player's usage of their weapon when the playerattempts to waste their ammunition by shooting at non-targets.

In some embodiments, the game logic 220 operation can receive as inputdata from the notification engine 218 and the gameplay penalizer 216operation. Using the data, the game logic 220 operation can be used makechanges to the game code so that a warning notification 108 appearswithin the gameplay of the player or to limit the game mechanics of theplayer to prevent the player from acting abusively in the gameplay.

FIG. 2B illustrates an embodiment of a method for using an abuseindicator model 212 to generate a gameplay player summary table 224using game context 202 gameplay data 204 a-204 n from a plurality ofplayers, inconsistent actions 228, and player tagged feedback 230 asinputs. In one embodiment, the abuse indicator model 212 implements oneor more machine learning operations that ingest the player gameplay data204 a-204 n, the game context 202, the inconsistent actions 228, and theplayer tagged feedback 230. In one example, the method includesaccessing player gameplay data 204 a-204 n from a game that is beingplayed by players 102 (e.g., Player 1, Player 2, Player N). In oneembodiment, the player gameplay data 204 a-204 n may include gameplaymetadata associated with each corresponding player in the game. Thegameplay metadata may include coded information, such as state data thatidentifies all of the actions, inputs, and moves made by the players 102during the gameplay.

In another embodiment, the method may further include parsing thegameplay data 204 a-204 n of each player to extract and identify thegame mechanics 206 a-206 n associated with the gameplay of the players.As noted above, the game mechanics are the basic actions, processes,rules, and control mechanisms that make up the gameplay for a videogame. For example, the game mechanic in a game can include variousmechanisms such as scoring points, jumping, maneuvering over obstacles,fighting enemies, defending against enemies, solving puzzles, managingresources, etc.

In another embodiment, the method may further include feature extraction208 a-208 n operations that are configured to receive the game mechanicsdata 206 a-206 n to identify various features in the game mechanics.After the feature extraction 208 a-208 n operation identifies thefeatures associated with the game mechanics 206 a-206 n in the gameplay,a classifier 210 a-210 n can be configured to classify the featuresusing one or more classifiers.

In some embodiments, the method flows to the abuse indicator model 212which is configured to receive as inputs the game context 202 so thatthe model knows what is occurring in the game, the classified featuresfrom classifier 210 a-210 n, the inconsistent actions 228, and theplayer tagged feedback 230. In another embodiment, other inputs that arenot direct inputs or lack of input/feedback, may also be taken as inputsto the abuse indicator model 212. For example, a player's accolades andother data associated with the player can be taken as inputs to theabuse indicator model 212. The abuse indicator model 212 may use amachine learning that is used to predict whether the player's actions inthe gameplay are abusive or consistent with the intent of the gameplay.The abuse indicator model 212 may also identify patterns andsimilarities based on the noted inputs. Using the patterns andsimilarities, the abuse indicator model 212 may infer whether a specificaction of a player is characterized as abusive.

As noted above, the each of the gameplay game mechanics 226 may includea plurality of inconsistent actions 228 that are predefined to beinconsistent with how the game is intended to be played. Inconsistentactions may be programmed or coded into a database, which can be used todetermine if such action is inconsistent with a game mechanic forspecific contextual scenarios. In other embodiments, the player taggedfeedback 230 may include feedback provided by other players during thegameplay. The player tagged feedback 230 can include various actionscommitted by the player during the gameplay that the other players inthe game identify as inconsistent actions. For example, an action sceneincludes a “Boss Fight” where the objective of the players is to shootthe villain character. Using the classified features from classifier 210a-210 n, the game context 202, the inconsistent actions 228, and theplayer tagged feedback 230, the abuse indicator model 212 is used todetermine that the shooting accuracy rate for player 1, player 2, andplayer N, is 95.4%, 93.1%, and 13.5%, respectively. Since the shootingaccuracy rate for player N is significantly lower than the shootingaccuracy rate for player 1 and player 2, it can be inferred that playerN acted abusively during the “Boss Fight” action scene.

In some embodiments, the method then flows to the gameplay playersummary table 224 where the output of the abuse indicator model 212 canbe information used for rendering the gameplay player summary table 224.In some embodiments, the gameplay player summary table 224 may includeinformation related to the gameplay of the players 102, performancemetrics in various action scenes, actions scenes where the player isidentified as abusive, etc.

FIG. 3 illustrates an embodiment of a system generating a player profile302 a-302 n for a given player using player gameplay data 204 a-204 nand a player profile model 301 a-301 n. In one embodiment, the playerprofile model 301 a-301 n implements one or more machine learningoperations that ingest the player gameplay data 204 a-204 n. The playergameplay data 204 a-204 n may include gameplay metadata and a variety ofinformation associated with all the games that the player has played inthe past. For example, the player gameplay data 204 a-204 n may includeinformation such as the type of games played, total time played, totalwins and losses, actions performed by the players, points scored, goalsearned, interactions between the players, progression in the game, etc.In one embodiment, the player profile model 301 a-301 n is configured toprocess metadata produced by the game, which can be parsed to identifyspecific features that relate to the actions of the player 102.

In some embodiments, the player profile model 301 a-301 n can be used togenerate a player profile 302 a-302 n for a particular player and topredict various gameplay tendencies of the player. In one embodiment,the player profile model 301 a-301 n can process the above noted inputto identify features associated with the video games played by theplayer in order to classify the features, using one or more classifiers.The classified features are then used by a machine learning engine topredict a player's gameplay tendencies for various types of video games.The output of the player profile model 301 a-301 n can be informationused for creating a player profile 302 a-302 n for a given player. Theplayer profile 302 a-302 n may include attributes and characteristics ofthe player such as gaming experience, gameplay history, viewing history,gaming skill level, preferences, interests, disinterests, etc. In someembodiments, the player profile 302 a-302 n may include informationrelated to the player's tendencies and habits during gameplay, e.g.,chat spamming, failing a team objective intentionally, misusing aweapon, etc.

In one embodiment, knowing a player's abusive tendencies can allow thesystem to proactively take action before the abusive act occurs, e.g.,limit the game mechanics of the player's gameplay or warn the player inadvance. For example, the player profile 302 a-302 n of a playerindicates that the player tends to intentionally interfere with thegameplay of teammates when playing a sports game. When the player playsa soccer game, the system may generate a warning notification at thestart of the gameplay to remind the player to not interfere with thegameplay of the teammates, e.g., do not trip teammates or steal thesoccer ball from a teammate. In some embodiments, instead of generatinga warning notification to notify the player, the game mechanics of theplayer can be limited. For example, the player's ability to trip ateammate or to steal the soccer ball from a teammate can be applied.

FIG. 4A illustrates an embodiment of a game mechanics grid 402 for agame played by a player 102. In one embodiment, the game mechanics grid402 can include a list of game mechanics 206 associated with the gameplayed by the player, a description 406 associated with thecorresponding game mechanic 206, various types of abusive actions 408that can be committed by the player, an abusive action score 410 that iscalculated based on the abusive actions committed by the player, athreshold value 412 associated with the game mechanic, and an evaluationof whether the abusive action score 410 exceeds the threshold value 412(e.g., 414).

As noted above, the game mechanics are the basic actions, processes,rules, and control mechanisms that make up gameplay for a video game. Asillustrated in FIG. 4A, for a particular game, the game mechanics 206may include various mechanics such as points scored, prisoner rescued,obstacle course completion, relay race, enemies attacked, damagedacquired, etc. The game mechanics 206 may vary and depend on the gamebeing played by the player. For each game mechanic 206, the system maykeep track of the plurality of abusive actions 408 that a player 102 maycommit during the gameplay. For example, as illustrated on the gamemechanics grid 402, the abusive actions 408 include a total of fivecategories. These categories include failing intentionally (e.g.,hitting a volleyball out of bounds), misuse of a game mechanic (e.g.,using a flash grenade on a teammate), overuse of a game mechanic (e.g.,wasting ammunition), spamming (e.g., flooding game chat system withemoticons), and complaints (e.g., received by teammates). In general,the abusive actions are actions that are inconsistent with the intent ofthe gaming activity and are intended to irritate or harass other playerswithin the game. In some embodiments, during the gameplay of the player,the system keeps track of the player's action during the gameplay andautomatically tags an action as abusive when the player commits anabusive action. In one embodiment, other players in the game can tag anaction of the player as abusive when the player commits an abusiveaction.

As illustrated in FIG. 4A, game mechanic GM-7 involves the player'sdefense against enemies. As illustrated on the game mechanics grid 402,the player failed intentionally a total of 4 times (e.g., did not defendagainst enemy attacks) and overused a game mechanic in the game a totalof 2 times (e.g., wasted weapon ammunition). Accordingly, an abusiveaction score for game mechanic GM-7 can be determined by taking thesummation of the total abusive actions (e.g., Σ(4+2)=6) and dividing itby the total number of abusive action categories (e.g., 5). As a result,the abusive action score for GM-7 results in a value of 1.2, e.g.,Σ(4+2)/(5)=1.2.

As noted above, the threshold value 412 associated with the gamemechanic can be compared to the abusive action score 410 to evaluatewhether the abusive action score 410 exceeds the threshold value 412.For example, game mechanic GM-7 has a threshold value of 0.75 and theabusive action score for GM-7 resulted in a calculated value of 1.2.Since the abusive action score exceeds the threshold value, the player102 can be identified as an abusive player and appropriate measures canbe taken to prevent the abusive player from committing actions that arecharacterized as abusive (e.g., limiting game mechanics, warning player,etc.).

In some embodiments, the game mechanics grid 402 can be used by adeveloper to track and monitor the abusive actions committed by theplayer 102 during the gameplay of the player. The game mechanics grid402 can be an efficient tool in helping developers identify possibleabusive players because the game mechanics grid 402 can track variousabusive acts of a player which can minimize the amount of data that adeveloper may have to sort through. In one embodiment, a developer mayproactively decide to take disciplinary action (e.g., warning theplayer, limiting game mechanics of the player, etc.) before the abusiveaction score 410 exceeds the corresponding threshold value 412. In someembodiments, the game mechanics grid 402 can be used by developers todetermine whether a player is a good faith player and acts in accordancewith the rules and guidelines of the game. For example, after the end ofa game session, a player with an abusive action score 410 that issignificantly lower than the threshold value 412 may be identified asgood faith player. Accordingly, the game mechanics grid 402 can be usedto distinguish between abusive players and good faith players.

In some embodiments, the game mechanics grid 402 can be used by adeveloper to identify trends and patterns associated with a particulargame mechanic. For example, for a particular game mechanic that involvesshooting a moving target, the game mechanics grid 402 may indicate thatthe majority of the players in the game intentionally failed to shoot atthe target. However, this may be false because the moving target may bemoving too fast and it may be difficult for most players to successfullyhit the target. Accordingly, a developer may investigate this particulargame mechanic associated with the game and determine whether changesneed to be made so that it does not appear that the players areintentionally failing to shoot at the target (e.g., increasing thethreshold value, adjusting game code to make it easier hit the movingtarget, etc.).

FIG. 4B is an embodiment illustrating a timeline 416 with a gamemechanics grid 402 being continuously updated throughout a game session.In one embodiment, during a game session of the player 102, the gamemechanics grid 402 is generated for the player 102 when the game sessionbegins (e.g., time t0) and is continuously updated throughout the gamesession until the game session ends (e.g., time tend). For example, asillustrated in FIG. 4B, at time t2, the game mechanics grid 402 a can beaccessed to determine whether the player is committing any abusiveactions during the gameplay and to determine whether the threshold valueassociated with the game mechanics has been exceeded. As the gameplay ofthe player 102 progresses, the game mechanics grid may continue tochange and may vary at any point in time. Accordingly, as shown in FIG.4B, the game mechanics grid 402 b and 402 c can be accessed at time t6and t10, respectively, to determine whether there are any changes to thegame mechanics grid. In one embodiment, the game mechanics grid mayreset after each game session ends, after an action scene ends, or aftera level is completed. In some embodiments, the game mechanics grid doesnot reset and is continuous for the entire gameplay of the player.

FIG. 5 is an embodiment illustrating correlating accolades that arepresented to a player 102 during a game to a specific game context inthe game. In some embodiments, accolades may be given to a player 102during a gameplay session of the player or after a game session ends.The accolades may be given to a player 102 by teammates of the player orby players on the opposing team. As shown in FIG. 5, accolades 502 a-502n are unaligned with game context 202 a-202 n because the accolades aregiven at a point in time after the game context occurs. Because of themisalignment, this may cause inaccuracies when determining which gamecontext the accolades are associated with.

For example, during the gameplay of the player involving a motocrossrace, the player may perform a series of actions. As illustrated in FIG.5, game context 202 a represents a state in the game when the playerjumps off a ramp, game context 202 b represents a state in the game whenthe player takes the lead in the race, and game context 202 n representsa state in the game when the player crashes and looses the lead in therace. Accordingly, the system may be configured to correlate theaccolades with the appropriate game context. As a result, as shown inFIG. 5, accolade 502 a is aligned to correspond to game context 202 a(e.g., player jumping off a ramp) and accolade 502 n is aligned tocorrespond to the game context 202 b (e.g., player taking the lead inthe race). In one embodiment, correlating the accolades and the gamecontext can be performed by a machine learning model that has beentrained to know the relative delays between the two datasets or based onthe context of the gameplay.

FIG. 6 illustrates an embodiment of a player accolades table 602 for aplurality of players 102. In one embodiment, the player accolades table602 can include a list of players 102 that participated in the gameplay,an action scene 606 associated with the gameplay, accolades given 608 toa player, an average accolade score 610, and an evaluation of whetherthe player's performance is characterized as abusive (e.g., 612). Asillustrated, the gameplay associated with players 102 a-102 n mayinclude various action scenes such as boss fight, ninja fight in thefield, rescue mission, battling Poseidon, climbing latter, etc. As notedabove, in some embodiments, accolades may be given to a player duringthe gameplay or after a game session ends. In one embodiment, theaccolades may be given by a player playing the game or a viewer watchingthe game. In one embodiment, as shown in FIG. 6, positive accolades(e.g., arrow pointed up) and negative accolades (e.g., arrow pointeddown) can be given to a player, and a maximum of five positive ornegative accolades can be awarded to a given player.

For example, as illustrated in FIG. 6, player 1 is given a total ofthree positive accolades for the boss fight action scene, one positiveaccolade for the ninja fight action scene, five positive accolades forthe rescue mission action scene, two positive accolades for the battlingPoseidon action scene, and four negative accolades for the climbingladder action scene. In some embodiments, the average accolade score 610corresponding to an action scene in the gameplay can be calculated forthe player. The average accolade score 610 is an average of all theaccolades given to a player for a specific action scene. For example,the average accolades score 610 corresponding to the rescue missionaction scene for player 1 results in a value of 4.5. In another example,the average accolades score 610 corresponding to the climbing ladderaction scene results in a value of −3.5. In one embodiment, whencalculating the average accolades score 610, negative accolades arerepresented by negative values (e.g., three negative accolades=−3) whichcan result in a negative accolades score.

In some embodiments, the average accolades score 610 can be used toevaluate whether the player's performance in a specific action scene ischaracterized as abusive, e.g., 612. In one embodiment, the averageaccolades score 610 can be compared to a specified threshold value todetermine whether the gameplay performance of the player ischaracterized as abusive. In one example, as illustrated in FIG. 6, anaverage accolade score that is less than zero is considered abusive, andan average accolade score that greater than zero is not consideredabusive. Accordingly, a player's average accolades score 610 can be usedto help determine whether a player is an abusive player.

In some embodiments, the accuracy and credibility of a player's averageaccolades score can be determined based on the players who are awardingthe accolades. For example, if a player has a high average accoladesscore (e.g., 4.9/5) and the accolades were awarded by abusive players,it can be inferred that the player's average accolades score may befalse or inaccurate. Accordingly, developers may investigate theaccolades awarded to the player by the abusive player to determinewhether the actions of the player are consistent with acts that arecharacterized as receiving positive accolades.

FIG. 7 illustrates a method for identifying an abusive player in a gameduring a game session. In one embodiment, the method includes anoperation 702 that receives gameplay data for a game played by theplayer 102. The method flows to operation 704 where the operation isconfigured to process a plurality of game mechanics of the game as theplayer provides input for one or more of the plurality of gamemechanics. For example, the player may be playing a multiplayer gamewhere the player is competing in a volleyball tournament. The method mayidentify and process various game mechanics associated with the gameplaysuch as scoring points, striking the ball over the net, preventing theball from hitting the ground, etc. While the player is playing thevolleyball game, the player is providing a plurality of input associatedwith the game mechanics of the game, e.g., passing the ball, spiking theball, blocking the ball, serving the ball, etc.

The method flows to operation 706 where the operation is configured toprocess abusive action scores for each of the plurality of gamemechanics. In some embodiments, the abusive action scores have a numberof tagged actions that are inconsistent with predefined use of saidplurality of game mechanics based a game context of the gameplay of thegame. Generally, the tagged actions that are inconsistent withpredefined use of the game mechanics are contrary with the intent of thegaming activity which tends to irritate or harass other players in thegame. For example, as illustrated in FIG. 4A (e.g. abusive actions 408),actions that are inconsistent with the predefined use of game mechanicscan include acts such as failing intentionally, misusing game mechanics,overusing game mechanics, spamming, complaining (e.g., receivingcomplaints or excessive complaining). As the gameplay progresses, when aplayer commits an act that is inconsistent with the predefined use ofthe game mechanics, the act is tagged to and used to process the abusiveaction scores. In other embodiments, additional examples of inconstantactions and abusive acts may include include kill stealing, purposefullyviolating rules or guidelines, exploiting bugs in the game, playing slowand ineffectively, deliberately performing actions detrimental to otherteam members' game performance, etc.

At operation 708, the operation is configured to determine whether theabusive action score exceeds the threshold value for any of the gamemechanics of the game. For example, referring to the game mechanics grid402 in FIG. 4A, various acts of abusive behavior (e.g., 408) areidentified and tagged to determine the number of times a player 102commits an abusive behavior for a corresponding game mechanic. Forexample, for game mechanic GM-N (e.g., weapons acquired), the playercommitted a total of 6 acts of abusive behavior. In particular, theplayer 102 failed intentionally a total of 2 times (e.g., did notacquire updated weapon when given the opportunity), spammed a total of 2times (e.g., submitted excessive emoticons in chat channel), andreceived a total of 2 complaints from teammates. Accordingly, theabusive action score for mechanic GM-N resulted in a calculated value of1.2 (e.g., Σ(2+2+2)/(5)=1.2). Since the abusive action score exceeds thethreshold value (e.g., 1.0), the player 102 can be identified as anabusive player. As a result, once the abusive player is identified, themethod flows to operation 710. However, if the abusive action score doesnot exceed the corresponding threshold value, the method flows back tooperation 706 where the operation is configured to continue processingthe abusive actions scores for each of the game mechanics.

At operation 710, the operation is configured to generate a warningnotification 108 and to notify the player 102 that the player isidentified as an abusive player. In one embodiment, the warningnotification 108 can appear on the monitor 106 of the player to notifythe player. The warning notification 108 can include a message to putthe abusive player on notice that the player has been identified as anabusive player. In some embodiments, the warning notification 108 mayinclude specific instructions to request the abusive player to restrainfrom performing a specific abusive act, e.g., don't hit ball out ofbounds, don't waste ammunition, don't shoot teammate, don't useexcessive emoticons, etc. For example, referring to FIG. 1, player 102 ais identified as an abusive player and the warning notification 108appears on the monitor 106 a which includes the message, “Warning! Youare identified as an abusive player. Don't hit ball out of bounds.”

The method flows to operation 712 where the operation is configured todetermine whether the abusive player complied with the warningnotification 108. If the abusive player is compliant with the requestindicated in the warning notification 108, the method flows back tooperation 706 where the operation is configured to continue processingthe abusive actions scores for each of the game mechanics. However, ifthe abusive player ignores the request indicated in the warningnotification 108 and continues to commit acts that are characterized asabusive, the method flows to operation 714.

At operation 714, the operation is configured to limit player gamemechanics associated with the gameplay. In one embodiment, operation 714can be configured to change the operation of the game for the abusiveplayer by adjusting the game code to limit specific game mechanics inthe gameplay of the player. In one embodiment, operation 714 can beconfigured to adjust the game code to prevent or limit the abusiveplayer from performing various gameplay functionalities such as killinga teammate, hitting a ball out of bounds, spamming the chat channel withemoticons, etc.

FIG. 8 illustrates components of an example device 800 that can be usedto perform aspects of the various embodiments of the present disclosure.This block diagram illustrates a device 800 that can incorporate or canbe a personal computer, video game console, personal digital assistant,a server or other digital device, suitable for practicing an embodimentof the disclosure. Device 800 includes a central processing unit (CPU)802 for running software applications and optionally an operatingsystem. CPU 802 may be comprised of one or more homogeneous orheterogeneous processing cores. For example, CPU 802 is one or moregeneral-purpose microprocessors having one or more processing cores.Further embodiments can be implemented using one or more CPUs withmicroprocessor architectures specifically adapted for highly paralleland computationally intensive applications, such as processingoperations of interpreting a query, identifying contextually relevantresources, and implementing and rendering the contextually relevantresources in a video game immediately. Device 800 may be a localized toa player playing a game segment (e.g., game console), or remote from theplayer (e.g., back-end server processor), or one of many servers usingvirtualization in a game cloud system for remote streaming of gameplayto clients.

Memory 804 stores applications and data for use by the CPU 802. Storage806 provides non-volatile storage and other computer readable media forapplications and data and may include fixed disk drives, removable diskdrives, flash memory devices, and CD-ROM, DVD-ROM, Blu-ray, HD-DVD, orother optical storage devices, as well as signal transmission andstorage media. User input devices 808 communicate user inputs from oneor more users to device 800, examples of which may include keyboards,mice, joysticks, touch pads, touch screens, still or videorecorders/cameras, tracking devices for recognizing gestures, and/ormicrophones. Network interface 814 allows device 800 to communicate withother computer systems via an electronic communications network, and mayinclude wired or wireless communication over local area networks andwide area networks such as the internet. An audio processor 812 isadapted to generate analog or digital audio output from instructionsand/or data provided by the CPU 802, memory 804, and/or storage 806. Thecomponents of device 800, including CPU 802, memory 804, data storage806, user input devices 808, network interface 810, and audio processor812 are connected via one or more data buses 822.

A graphics subsystem 820 is further connected with data bus 822 and thecomponents of the device 800. The graphics subsystem 820 includes agraphics processing unit (GPU) 816 and graphics memory 818. Graphicsmemory 818 includes a display memory (e.g., a frame buffer) used forstoring pixel data for each pixel of an output image. Graphics memory818 can be integrated in the same device as GPU 808, connected as aseparate device with GPU 816, and/or implemented within memory 804.Pixel data can be provided to graphics memory 818 directly from the CPU802. Alternatively, CPU 802 provides the GPU 816 with data and/orinstructions defining the desired output images, from which the GPU 816generates the pixel data of one or more output images. The data and/orinstructions defining the desired output images can be stored in memory804 and/or graphics memory 818. In an embodiment, the GPU 816 includes3D rendering capabilities for generating pixel data for output imagesfrom instructions and data defining the geometry, lighting, shading,texturing, motion, and/or camera parameters for a scene. The GPU 816 canfurther include one or more programmable execution units capable ofexecuting shader programs.

The graphics subsystem 814 periodically outputs pixel data for an imagefrom graphics memory 818 to be displayed on display device 810. Displaydevice 810 can be any device capable of displaying visual information inresponse to a signal from the device 800, including CRT, LCD, plasma,and OLED displays. Device 800 can provide the display device 810 with ananalog or digital signal, for example.

It should be noted, that access services, such as providing access togames of the current embodiments, delivered over a wide geographicalarea often use cloud computing. Cloud computing is a style of computingin which dynamically scalable and often virtualized resources areprovided as a service over the Internet. Users do not need to be anexpert in the technology infrastructure in the “cloud” that supportsthem. Cloud computing can be divided into different services, such asInfrastructure as a Service (IaaS), Platform as a Service (PaaS), andSoftware as a Service (SaaS). Cloud computing services often providecommon applications, such as video games, online that are accessed froma web browser, while the software and data are stored on the servers inthe cloud. The term cloud is used as a metaphor for the Internet, basedon how the Internet is depicted in computer network diagrams and is anabstraction for the complex infrastructure it conceals.

A game server may be used to perform the operations of the durationalinformation platform for video game players, in some embodiments. Mostvideo games played over the Internet operate via a connection to thegame server. Typically, games use a dedicated server application thatcollects data from players and distributes it to other players. In otherembodiments, the video game may be executed by a distributed gameengine. In these embodiments, the distributed game engine may beexecuted on a plurality of processing entities (PEs) such that each PEexecutes a functional segment of a given game engine that the video gameruns on. Each processing entity is seen by the game engine as simply acompute node. Game engines typically perform an array of functionallydiverse operations to execute a video game application along withadditional services that a user experiences. For example, game enginesimplement game logic, perform game calculations, physics, geometrytransformations, rendering, lighting, shading, audio, as well asadditional in-game or game-related services. Additional services mayinclude, for example, messaging, social utilities, audio communication,game play replay functions, help function, etc. While game engines maysometimes be executed on an operating system virtualized by a hypervisorof a particular server, in other embodiments, the game engine itself isdistributed among a plurality of processing entities, each of which mayreside on different server units of a data center.

According to this embodiment, the respective processing entities forperforming the may be a server unit, a virtual machine, or a container,depending on the needs of each game engine segment. For example, if agame engine segment is responsible for camera transformations, thatparticular game engine segment may be provisioned with a virtual machineassociated with a graphics processing unit (GPU) since it will be doinga large number of relatively simple mathematical operations (e.g.,matrix transformations). Other game engine segments that require fewerbut more complex operations may be provisioned with a processing entityassociated with one or more higher power central processing units(CPUs).

By distributing the game engine, the game engine is provided withelastic computing properties that are not bound by the capabilities of aphysical server unit. Instead, the game engine, when needed, isprovisioned with more or fewer compute nodes to meet the demands of thevideo game. From the perspective of the video game and a video gameplayer, the game engine being distributed across multiple compute nodesis indistinguishable from a non-distributed game engine executed on asingle processing entity, because a game engine manager or supervisordistributes the workload and integrates the results seamlessly toprovide video game output components for the end user.

Users access the remote services with client devices, which include atleast a CPU, a display and I/O. The client device can be a PC, a mobilephone, a netbook, a PDA, etc. In one embodiment, the network executingon the game server recognizes the type of device used by the client andadjusts the communication method employed. In other cases, clientdevices use a standard communications method, such as html, to accessthe application on the game server over the internet.

It should be appreciated that a given video game or gaming applicationmay be developed for a specific platform and a specific associatedcontroller device. However, when such a game is made available via agame cloud system as presented herein, the user may be accessing thevideo game with a different controller device. For example, a game mighthave been developed for a game console and its associated controller,whereas the user might be accessing a cloud-based version of the gamefrom a personal computer utilizing a keyboard and mouse. In such ascenario, the input parameter configuration can define a mapping frominputs which can be generated by the user's available controller device(in this case, a keyboard and mouse) to inputs which are acceptable forthe execution of the video game.

In another example, a user may access the cloud gaming system via atablet computing device, a touchscreen smartphone, or other touchscreendriven device. In this case, the client device and the controller deviceare integrated together in the same device, with inputs being providedby way of detected touchscreen inputs/gestures. For such a device, theinput parameter configuration may define particular touchscreen inputscorresponding to game inputs for the video game. For example, buttons, adirectional pad, or other types of input elements might be displayed oroverlaid during running of the video game to indicate locations on thetouchscreen that the user can touch to generate a game input. Gesturessuch as swipes in particular directions or specific touch motions mayalso be detected as game inputs. In one embodiment, a tutorial can beprovided to the user indicating how to provide input via the touchscreenfor gameplay, e.g. prior to beginning gameplay of the video game, so asto acclimate the user to the operation of the controls on thetouchscreen.

In some embodiments, the client device serves as the connection pointfor a controller device. That is, the controller device communicates viaa wireless or wired connection with the client device to transmit inputsfrom the controller device to the client device. The client device mayin turn process these inputs and then transmit input data to the cloudgame server via a network (e.g. accessed via a local networking devicesuch as a router). However, in other embodiments, the controller canitself be a networked device, with the ability to communicate inputsdirectly via the network to the cloud game server, without beingrequired to communicate such inputs through the client device first. Forexample, the controller might connect to a local networking device (suchas the aforementioned router) to send to and receive data from the cloudgame server. Thus, while the client device may still be required toreceive video output from the cloud-based video game and render it on alocal display, input latency can be reduced by allowing the controllerto send inputs directly over the network to the cloud game server,bypassing the client device.

In one embodiment, a networked controller and client device can beconfigured to send certain types of inputs directly from the controllerto the cloud game server, and other types of inputs via the clientdevice. For example, inputs whose detection does not depend on anyadditional hardware or processing apart from the controller itself canbe sent directly from the controller to the cloud game server via thenetwork, bypassing the client device. Such inputs may include buttoninputs, joystick inputs, embedded motion detection inputs (e.g.accelerometer, magnetometer, gyroscope), etc. However, inputs thatutilize additional hardware or require processing by the client devicecan be sent by the client device to the cloud game server. These mightinclude captured video or audio from the game environment that may beprocessed by the client device before sending to the cloud game server.Additionally, inputs from motion detection hardware of the controllermight be processed by the client device in conjunction with capturedvideo to detect the position and motion of the controller, which wouldsubsequently be communicated by the client device to the cloud gameserver. It should be appreciated that the controller device inaccordance with various embodiments may also receive data (e.g. feedbackdata) from the client device or directly from the cloud gaming server.

It should be understood that the various embodiments defined herein maybe combined or assembled into specific implementations using the variousfeatures disclosed herein. Thus, the examples provided are just somepossible examples, without limitation to the various implementationsthat are possible by combining the various elements to define many moreimplementations. In some examples, some implementations may includefewer elements, without departing from the spirit of the disclosed orequivalent implementations.

Embodiments of the present disclosure may be practiced with variouscomputer system configurations including hand-held devices,microprocessor systems, microprocessor-based or programmable consumerelectronics, minicomputers, mainframe computers and the like.Embodiments of the present disclosure can also be practiced indistributed computing environments where tasks are performed by remoteprocessing devices that are linked through a wire-based or wirelessnetwork.

Although the method operations were described in a specific order, itshould be understood that other housekeeping operations may be performedin between operations, or operations may be adjusted so that they occurat slightly different times or may be distributed in a system whichallows the occurrence of the processing operations at various intervalsassociated with the processing, as long as the processing of thetelemetry and game state data for generating modified game states andare performed in the desired way.

One or more embodiments can also be fabricated as computer readable codeon a computer readable medium. The computer readable medium is any datastorage device that can store data, which can be thereafter be read by acomputer system. Examples of the computer readable medium include harddrives, network attached storage (NAS), read-only memory, random-accessmemory, CD-ROMs, CD-Rs, CD-RWs, magnetic tapes and other optical andnon-optical data storage devices. The computer readable medium caninclude computer readable tangible medium distributed over anetwork-coupled computer system so that the computer readable code isstored and executed in a distributed fashion.

Although the foregoing embodiments have been described in some detailfor purposes of clarity of understanding, it will be apparent thatcertain changes and modifications can be practiced within the scope ofthe appended claims. Accordingly, the present embodiments are to beconsidered as illustrative and not restrictive, and the embodiments arenot to be limited to the details given herein, but may be modifiedwithin the scope and equivalents of the appended claims.

What is claimed is:
 1. A method for identifying an abusive player in agame, comprising: receiving gameplay data for a player during gameplayof the game; processing a plurality of game mechanics of the game as theplayer provides input for one or more of said plurality of gamemechanics; processing abusive action scores for each of the plurality ofgame mechanics, the abusive action scores have a number of taggedactions that are inconsistent with predefined use of said plurality ofgame mechanics based on a game context of the gameplay of the game;qualifying the player as abusive in regard to one or more of theplurality of game mechanics based on one or more of the abusive actionsscores exceeding a threshold during a session of the gameplay of thegame; and generating an interface for presenting the processed abusiveaction scores, the interface is configured to include the plurality ofgame mechanics and the tagged actions during the session of thegameplay, the interface being updated in substantial real time based onchanges in the gameplay.
 2. The method of claim 1, wherein the game is amultiplayer game and the player is one of a plurality of players engagedin said gameplay during the session, wherein one or more of said taggedactions are received from other players when playing with the player inthe multiplayer game.
 3. The method of claim 1, wherein one or more ofsaid tagged actions are automatically identified by an abuse indicatormodel that monitors use of game mechanics by the player based on saidgame context, wherein the abuse indicator model is configured to processas input a plurality of inconsistent actions for one or more of saidplurality of game mechanics.
 4. The method of claim 3, wherein saidplurality of inconsistent actions include ones predefined asinconsistent or learned to be inconsistent based on feedback from one ormore players tagging actions as inconsistent.
 5. The method of claim 1,further comprising, generating a warning notification to notify theplayer that the player is qualified as an abusive player when the one ormore of the abusive actions scores exceeds the threshold.
 6. The methodof claim 1, further comprising, adjusting game code of the game to limitthe one or more of the plurality of game mechanics when the one or moreof the abusive actions scores exceeds the threshold.
 7. The method ofclaim 1, wherein the processing the abusive action scores is furtherbased on processing features from the plurality of game mechanics andthe game context of the gameplay, the features being classified and usedto build an abuse indicator model that identifies relationships betweenthe plurality of game mechanics and the game context.
 8. The method ofclaim 1, wherein the qualifying the player as abusive is further basedon processing by an abuse indicator model a profile of the player, theprofile of the player identifying tendencies of the player in thegameplay and other games played by the player.
 9. The method of claim 1,wherein the qualifying the player as abusive is further based onprocessing by an abuse indicator model accolades received by the player,said accolades are received from other players during the session of thegameplay or after the session of the gameplay ends.
 10. The method ofclaim 9, further comprising, correlating the accolades received by theplayer to a corresponding game context of the gameplay.
 11. The methodof claim 1, wherein the abusive action scores change over time duringthe session of the gameplay based on the number of tagged actions.
 12. Anon-transitory computer-readable storage medium storing a computerprogram, the computer-readable storage medium comprising: programinstructions for receiving gameplay data for a player during gameplay ofthe game; program instructions for processing a plurality of gamemechanics of the game as the player provides input for one or more ofsaid plurality of game mechanics; program instructions for processingabusive action scores for each of the plurality of game mechanics, theabusive action scores have a number of tagged actions that areinconsistent with predefined use of said plurality of game mechanicsbased on a game context of the gameplay of the game; programinstructions for qualifying the player as abusive in regard to one ormore of the plurality of game mechanics based on one or more of theabusive actions scores exceeding a threshold during a session of thegameplay of the game, and program instructions for generating aninterface for presenting the processed abusive action scores, theinterface is configured to include the plurality of game mechanics andthe tagged actions during the session of the gameplay, the interfacebeing updated in substantial real time based on changes in the gameplay.13. The non-transitory computer-readable storage medium as recited inclaim 12, wherein the game is a multiplayer game and the player is oneof a plurality of players engaged in said gameplay during the session,wherein one or more of said tagged actions are received from otherplayers when playing with the player in the multiplayer game.
 14. Thestorage medium as recited in claim 12, wherein one or more of saidtagged actions are automatically identified by an abuse indicator modelthat monitors use of game mechanics by the player based on said gamecontext, wherein the abuse indicator model is configured to process asinput a plurality of inconsistent actions for one or more of saidplurality of game mechanics.
 15. The non-transitory computer-readablestorage medium as recited in claim 12, wherein said plurality ofinconsistent actions include ones predefined as inconsistent or learnedto be inconsistent based on feedback from one or more players taggingactions as inconsistent.
 16. The non-transitory computer-readablestorage medium as recited in claim 12, further comprising, programinstructions for generating a warning notification to notify the playerthat the player is qualified as an abusive player when the one or moreof the abusive actions scores exceeds the threshold.
 17. Thenon-transitory computer-readable storage medium as recited in claim 12,further comprising, program instructions for adjusting game code of thegame to limit the one or more of the plurality of game mechanics whenthe one or more of the abusive actions scores exceeds the threshold. 18.The non-transitory computer-readable storage medium as recited in claim12, wherein the qualifying the player as abusive is further based onprocessing by an abuse indicator model a profile of the player, theprofile of the player identifying tendencies of the player in thegameplay and other games played by the player.